Generating growth alternatives

ABSTRACT

The present invention is an apparatus and method for determining when a living animal reaches its optimum rate of growth. This information is then used to calculate the optimal parameters for achieving the maximum Return On Investment. The computer determines the optimal number of birds for a flock, type and amount of feed, length of time between hatching and sale to food processor, etc. The computer consists of a microprocessor, random access memory, a storage device, a keyboard, a computer screen, a printer, a math co-processor.

REFERENCE TO CO-PENDING APPLICATIONS

[0001] The present application is a continuation-in-part of U.S.application Ser. No. 08/289,652, filed Aug. 12, 1994, which is a filewrapper continuation of U.S. application Ser. No. 08/125,409, filed onSep. 22, 1993.

TECHNICAL FIELD

[0002] The present invention relates to generating optimized livingentity and edible tissue growth alternatives and amounts, and morespecifically to a method and apparatus for generating an inter-variableand temporal relationships between tissue growth factors of an animal inorder to optimize edible tissue output production given inherententerprise finance, resources, processing, and marketing constraints.

BACKGROUND

[0003] The economic optimization and viability of an enterprise dependson the ability to accurately analyze the relationship between the costof materials, services, and labor that are input into the enterprise andthe return that is achieved on the product that is output by theenterprise. In agribusiness industries that raise animals such aslivestock, poultry, marine animals, etc., the inputs include the animalitself, food, shelter, and services. The output, of course, is themarketable tissue components of the processed animal. One of the mostcritical relationships in optimizing the economic margins of anenterprise is the relationship between the controllable anduncontrollable factors that affect the rate at which the animal and itstissue components grow and the final size of the animal at marketingage. Thus, it is important to have a value-based food chain model thatdescribes the relationship between each of these factors and the rate ofgrowth of a population of animals.

[0004] Variables affecting the growth and yield of edible tissue ofanimals can be divided into genetic and non-genetic categories. Geneticvariables are fixed and are reflected by the growth potential of theindividual type of animal of interest. It will be appreciated by thoseskilled in the art that the growth rate of a animal is never higher andonly lower than the maximum potential. During its life, a animal seeksto achieve its genetic potential, but fails due to the impediment ofnon-genetic variables.

[0005] Non-genetic variables that are partially controllable by thecommercial operator can be divided further into living factors and foodfactors. Living factors encompass environmental conditions such astemperature, humidity, animal density, ventilation, disease conditions,air quality, etc. Food factors encompass the types and digested amountsof material that are ingested by a animal. One skilled in the art willappreciate that food factors can be controlled in a commercialenvironment through nutrition. The food factor reflects a major portionof the cost during the growth period.

[0006] To maximize an enterprise's before tax net margin, manyscientists have used models to simulate the growth of various types ofanimals. (see G. C. Emmans, “The Growth of Turkeys,” 21 Recent Advancesin Turkey Science, 135-166 (C. Nixey and T. C. Grey eds. 1989); H.Talpaz et al., “Dynamic Optimization Model for Feeding of Broilers,”Agric. Sys, 121-132 (1986); H. Talpaz et al., “Economic Optimization ofa Growth Trajectory for Broilers,” 70 Amer. J. Ag. Econ., 382-390(1988); P. E. Waibel et al., TURKS Program Agricultural ExtensionService (University of Minnesota 1985)). It will be appreciated that thevarious models represent efforts to take into account the incrediblycomplex and diverse structure of living entities, as well as theinnumerable variables that affect the living entities in theirenvironment.

[0007] One model that is used to describe animal growth is the Gompertzcurve (B. Gompertz, “On the Nature of the Function Expressive of the Lawof Human Mortality, and on a New Mode of Determining the Value of LifeContingencies,” Philos. Trans. Roy. Soc., 513-585 (1825)), which showsthe current mass weight as a function of age with known constantparameters. Gompertz curves have been used to describe the growth ofpoultry only in terms of a singular factor or characteristic such as agenetic characteristic, a living condition, or a food factor (G. C.Emmans, “The Growth of Turkeys,” 21 Recent Advances in Turkey Science,135-166 (C. Nixey and T. C. Grey eds. 1989); R. M. Gous et al., “ACharacterization of the Potential Growth Rate of Six Breeds ofCommercial Broiler,” 2 Proceedings of XIX World's Poultry Congress,20-24 (Amsterdam, The Netherlands, September 1992); N. B. Anthony etal., “Comparison of Growth Curves of Weight Selected Populations ofTurkeys, Quail and Chickens,” 70 Poultry Sci., 13-19 (1991)). However,because all the parameters are independent from one to another among allthe curves, each Gompertz curve can describe growth in terms of only oneset of conditions.

[0008] Because of the complexity of a life form, there is a need for amodel that describes growth alternatives in terms of a plurality ofdifferent conditions. Such a model would permit an accurate economicanalysis that allows a commercial operator to simultaneously(non-repetitive) optimize the relationship between the conditions andgrowth. In turn, the production of living animals would be more easilycontrolled in order to optimize production and hence maximize economicreturn.

SUMMARY

[0009] One advantage of the present invention is that it is based on thecorrelation between constant parameters among a multitude of Gompertzcurves, each describing the growth of an animal given a predeterminedcharacteristic. Thus, a commercial poultry operator can use theapparatus and method to simultaneously optimize growth and yield in aplurality of living and food conditions in order to maximize economicreturn.

[0010] The present invention generally relates to a modeling method andoperating a computer that computes the time trajectory that a bird canreach its optimum rate of growth with age. Using this information, thecomputer can simultaneously determine an appropriate size for a flock ofbirds, the type and amount of feed that should be fed to the flock, andthe age at which a flock should be sold to a food processor, in order tomaximize the profits realized by a commercial integrator who raises orsubcontracts meat production.

[0011] More specifically, the present invention is an apparatus foroptimizing the ratio between expenditures and rate of growth for livinganimals. This apparatus includes processing means for optimizing theratio between expenditures and the rate of growth for animals, whereinthe processing optimum rate of growth according to the equationW=Ae{circumflex over ( )}(−e{circumflex over ( )}(−k(t−t*))), where W isthe current body weight of the animal, A is the weight of the animal atphysical maturity, k is a growth rate factor, t is the current age ofthe animal, and t* is the age at which the animal has its maximum rateof growth, t* and k being statistically related.

[0012] The apparatus also includes memory means for storing datacorresponding to information about feed, information about thecharacteristics of the animals, and information generated by theprocessing means. The memory means is operationally coupled to the meanscalculates the optimum rate of growth with age at which the animals canexperience their processing means.

[0013] The present invention is also in the form of a method foroperating the apparatus. The method steps include calculating the timetrajectory at which the animal can experience its optimum rate of growthwith age according to the equation W=Ae{circumflex over( )}(−e(−k(t−t*))) where W is the current body weight of the animal, Ais the weight of the animal at physical maturity, k is a growth ratefactor, t is the current age of the animal, and t* is the age at whichthe animal has its maximum rate of growth, t* and k being statisticallyrelated. The method includes the additional step of storing datacorresponding to information about feed, information about thecharacteristics of the animals, and information generated by theprocessing means.

[0014] These and other advantages and capabilities, which characterizethe present invention, are pointed out with particularity in the claimsannexed hereof and forming a further part hereof. However, for a betterunderstanding of the invention, its advantages, and objects obtained byits use, reference should be made to the drawings, which form a furtherpart hereto, and to the accompanying descriptive matter, whichillustrates and describes a preferred embodiment of the presentinvention.

DESCRIPTION OF THE DRAWINGS

[0015]FIG. 1 is a graph showing the growth alternatives described by aGompertz curve.

[0016]FIG. 2 is a chart showing the values of and relationship betweenthe rate factor, k, and the inflection point, t*, for a variety ofstrains of birds.

[0017]FIG. 3 is a graph showing the relationship between the ratefactor, k, and the inflection point, t*, using the data that is includedin the chart of FIG. 2.

[0018]FIG. 4 is a functional block diagram of a multipurpose computeruseful for practicing the method of the present invention.

[0019] FIGS. 5-19 are menus, screen displays, and a sample report of apreferred embodiment computer program which implements the presentinvention.

[0020]FIG. 20 is a functional block diagram of program logic used toimplement the principles of the invention.

[0021]FIGS. 21a and 21 b set forth an information flow diagram for theprogram logic of FIG. 20.

[0022]FIGS. 22a-22 ai set forth a flow chart showing the detailedoperation of the program logic shown in FIGS. 20 and 21.

DETAILED DESCRIPTION

[0023] A preferred embodiment of the invention will be described indetail with reference to the Drawings, wherein like reference numeralsrepresent like parts and assemblies throughout the several views.Reference to the preferred embodiment does not limit the scope of theinvention which is limited only by the scope of the claims attachedhereto.

[0024] The present invention correlates equations that describe themultitude of Gompertz curves for various variables that describe thegrowth of living animals. The results of the correlation allow an animalprocessor to simultaneously optimize the ratio between expenditures andgrowth and thus optimize profit margins. In other words, the growth rateof the animal is substantially optimized when the market value of theanimal and the cost incurred from raising the animal maximizes thebefore tax net margin associated with raising the animal or populationof animals.

[0025] Additionally, the variable can describe both genetic andnon-genetic characteristics or factors involved with modeling the growthof the animals or the population of animals. The non-genetic variablesare substantially at their optimal values when the net margin ismaximized. Some examples of non-genetic characteristics that aredescribed by the non-genetic variable include body weight, populationdensity, nutrient composition of the feed, temperature, and humidity.

[0026] One skilled in the art will realize that the present inventionmay be used for any type of animal whose growth can be described by aGompertz curve. However, for purposes of description, the presentinvention is described in the context of poultry.

A. Theory

[0027] As shown in FIG. 1, a Gompertz curve represents mass as afunction of time, and is commonly used to represent the growth ofpoultry. The Gompertz curve that describes a growth pattern in Lairdform is as follows:

W=W ₀ e{circumflex over ( )}(L/k)(1−e{circumflex over ( )}(−kt))  (1)

[0028] where W is the current body weight, W₀ is the initial bodyweight, L is a constant, k is a constant, t is the current age of thebird, and {circumflex over ( )} represents an exponent. (Laird, A. K.1966. Postnatal growth of birds and mammals. Growth 30:349-363) Equation(1) can be rearranged as follows:

W=f(t)=W ₀ e{circumflex over ( )}((L/k)e{circumflex over( )}((−L/k)e{circumflex over ( )}(−kt))).  (2)

[0029] The limit of equation (2) as t→∞ is defined as:

lim f(t)=A=W ₀ e{circumflex over ( )}(L/k)  (3)

[0030] where A is the bird's mature body weight. Combining equation (2)and equation (3) results in the following equation:

W=Ae{circumflex over ( )}((−L/k)e{circumflex over ( )}(−kt)),  (4)

[0031] which can be written as follows:

W=Au  (5)

[0032] where

u=e{circumflex over ( )}((−L/k)e{circumflex over ( )}(−kt)).  (6)

[0033] Equation (4) can be rewritten as:

W=Ae{circumflex over ( )}(−Be{circumflex over ( )}(−kt))  (7)

[0034] where B=L/k.

[0035] From equation (7), the average daily gain is:

f′(t)=WkBe{circumflex over ( )}(−kt).  (8)

[0036] The rate at which the average daily gain changes is defined as:

f″(t)=k{circumflex over ( )}(2)BWe{circumflex over( )}(−kt)(Be{circumflex over ( )}(−kt)−1)  (9)

[0037] If f″(t)=0 at the age of maximum gain, then:

0=k{circumflex over ( )}(2)BWe{circumflex over ( )}(−kt*)(Be{circumflexover ( )}(−kt*)−1)

Be{circumflex over ( )}(−kt*)=1

B=e{circumflex over ( )}(kt*)  (10)

[0038] where t* is defined as the inflection point, which represents theage at which the maximum daily weight gain is achieved.

[0039] The constants t* and k govern the form of growth curve. Ifequation (10) is substituted into equation (7), then

W=Au  (11)

[0040] Where u=e{circumflex over ( )}(−e{circumflex over( )}(−k(t−t*))). Equation (11) shows that current body weight depends onmature weight A and u. Mature weight A is a genetically inherited value.Given fixed genetic conditions, the form of growth trajectory depends onu, i.e., the growth rate factor k and inflection point t*. Therefore,living conditions affect the form of growth trajectory through theparameters t* and k. The growth trajectory represents body weight overage.

[0041] Rate factor k and inflection point t* are independent of eachother among multiple growth curves even though they are constrained byequation (10) within one curve. Due to the simultaneous impact of livingconditions, the two parameters of equation (11) can not be used tooptimize growth by optimizing parameter k and t* independently.Independent optimization of parameter k and/or t* may result in faultycombinations of the two parameters in terms of describing animal growth.Their inter-relationship among different curves has to be established inorder to make equation (11) cover multiple curves so that it can be usedin an automated computer optimization process, i.e., either makeconstant k a function of the inflection point t* so that k=f(t*) or maket* a function of k so that t*=f(k).

[0042] The equations that are utilized in the program of the presentinvention are:

W=Ae{circumflex over ( )}(−e{circumflex over ( )}(−k(t−f(k))  (12)

[0043] which can be rewritten as:

W=Ae{circumflex over ( )}(−e{circumflex over ( )}(−f(t*)(t−t*)).  (13)

[0044] For simplicity, Equation (13) will be used for explanation.

[0045] When mature weight A and age t is known, only one variable t* isleft to predict body weight W in equation (13). The difference betweenequation (11) and equation (13) is that equation (11) represents onlyone growth curve and t* is a constant. However, equation (13) representsmultiple curves wherein t* is a variable that can be optimized in anoptimization process. Therefore, the relationship between k and t* mustbe defined. This relationship will be in the form of a function k=f(t*).

[0046] Experimental growth data for broilers, quails, and turkeys withdifferent genetic and environmental conditions have been obtained frompublic domain sources and summarized. This information is containedwithin the program of the present invention and can be used to definethe relationship between k and t*.

[0047] The body weight for male turkeys of age 0 to 18 weeks (Waibel, P.E., “Pelleting, fat, and protein levels in turkey diets.” 67 Proc. ofMaryland Nutrition Conference for Feed Manufactures, Mar. 16-17, (1989))and female turkeys of age 0 to 18 weeks (Waibel, P. E. et al.,“Factorial Study of Protein Level Sequence and Diet Energy/Pelleting onPerformance of Large White Hen Turkeys,” 68 reported in Poultry scienceAssociation Annual Meeting, University of Wisconsin, Madison. Jul. 24-28(1989)) are each comprised of 24 different protein sequence treatments.The body weights of each treatment at different ages was independentlyfitted into equation (11) and the corresponding value for k and t* wascalculated. These values are shown in FIG. 2. More specifically,constant k and t* were experimentally determined by (See Hurwitz, S. etal., “Estimation of the Energy Needs of Young Broiler Chicks,”Proceedings of the Meeting, Arkansas Nutrition Conference 16-21(Riverfront Hilton, North Little Rock, Ark., Sep. 10-12, 1991); Talpaz,H. et al., “Dynamic Optimization Model for Feeding of Broilers,” Agaric.Says, 121-132 (1986); Talpaz, H. et al., “Modeling of Dynamics ofAccelerated Growth Following Feed Restriction in Chicks,” 36 Agric.Sys., 125-135 (1991); Gous, R. M. et al., “A Characterization of thePotential Growth Rate of Six Breeds of Commercial Broiler,” 2Proceedings of XIX World's Poultry Congress, 20-24 (Amsterdam, TheNetherlands, September 1992); Emmans, G. C., “The Growth of Turkeys,” 21Recent Advances in Turkey Science, 135-166 (C. Nixey and T. C. Grey eds.1989); Anthony, N. B. et al., “Comparison of Growth Curves of WeightSelected Populations of Turkeys, Quail and Chickens,” 70 Poultry Sci.,13-19 (1991)) and fitted into equation (11) by mathematical methods thatare commonly known in the art. FIG. 2 also includes the values of B andL, which were calculated using equation (10). FIG. 3 is a graph in whichk is plotted against t*. The graph of FIG. 3 demonstrates therelationship of k=f(t*) and that the relationship between k and t* isnon-linear. Examining the graph of FIG. 3, one skilled in the art willrealize that statistical methods demonstrate that k=0.79878t*(−0.83747),where adjusted correlation coefficient r=0.9746.

[0048] Equation (13) can be rewritten as

W=Ae{circumflex over ( )}(−e{circumflex over( )}(−(0.79878t*(−0.83747)(t−t*)))).  (14)

[0049] This equation covers a multitude of growth curve possibilitiesand can be used for different types of poultry including turkey,broiler, duck, quail, etc. Given equation (13), constant t* is the onlyvariable to be affected by various living conditions.

[0050] Equations (12) and (13) reveal that the rate at which a birdgrows depends on only one variable—−t* or k. As discussed above, t* isthe age at which a bird has its maximum rate of gain and k is a growthrate factor. The earlier the age, the quicker the bird will grow to theweight at which it may be marketed. The commercial applications ofequation (12) or (13) will be very important tools in selecting the mostefficiently growing genotype of bird and in genetic breeding. Oneskilled in the art will appreciate that the present invention may alsohave applications related to the production of other types of animals aswell as vegetation.

[0051] Equation (13) can be utilized in optimizing poultry productionbecause it correlates multiple growth curves, which include a geneticpotential growth curve of the type shown in FIG. 1. A curve of this typeis required in order to implement a computer optimization process. Asdiscussed above, the genetic potential growth curve of FIG. 1 definesthe minimum age at which a bird's maximum growth rate is reached. Giventhe curve of FIG. 3, a computer can calculate optimum weight gain andaverage body weight for each feeding period of a flock of birds. Theweight gain and average body weight is then used to determine theoptimal living and food environments. The following example shows howthe potential weight gain can be modified by changing the density ofturkeys within a certain living space.

[0052] Change of weight gain=0.71556+7.9902 MDNSITY−57.765 MDNSITY2where r (correlation coefficient)=0.8846; overall p-value (possibilityvalue)=0.0006; and MDNSITY-body weight density ranged 0.03 to 0.06meter2/kg0.67. Similar predictions can be derived by establishing theeffect of temperature, humidity, ventilation, etc. on weight gain.

[0053] In addition to predicting physical mass of the entire bird, theinflection point t* can be used to predict the growth of each componentpart of a bird's body. The following is an example for turkeys:

[0054] Breast (% of Eviscerated carcass)=67.121−2.2824 Sex+0.37094Age−0.00093294 Age2−93116 ln(Age)−0.14238 t* where r=0.843; and p-valueof coefficient t*=0.0000.

[0055] Thigh (% of Eviscerated carcass)=14.6+0.056919 Age−0.00022113Age2−0.026625 t* where r=0.875; and p-value of coefficient t*=0.0000.

[0056] Wing (% of Eviscerated carcass)=26.399−2.3552 Sex+0.10141Age−0.0018162 Age2+0.0000064398 Age3−0.10284 t* where r=0.90; p-value ofcoefficient t*=0.0000.

[0057] Neck (% of Eviscerated carcass)=18.056−2.1653 Sex−0.0095747Age−0.085037 t* where r=0.6367; and p-value of coefficient t*=0.0000where Sex−1 for male, 2 for female; age=age in days; t*=inflection point(days); r=correlation coefficient; and p-value=possibility value.

[0058] All the above regression equations show that the inflection pointt* has a significant effect on dependent variables as indicated by thesmall number of p-values.

B. Commercial Embodiment

[0059] As one skilled in the art will realize and as shown in FIG. 4,the present invention is preferably utilized with a personal or workstation computer (hereinafter PC) that is based on Intel's 80486microprocessor 20 with a 66 MHz clock, Intel's PENTIUM™ microprocessor,a high speed RISC processor, or any other similar microprocessor. Thecomputer also preferably has a math co-processor 22 for completingmathematical computations. The computer also includes a keyboard 24,screen 26, printer 28, random access memory 30, and a storage device 32.The storage device 32 may include magnetic means (i.e., floppy diskdrive, hard drive, or tape drive), optical disk means, firm ware, or anyother appropriate storage means. The storage device 32 is used to storethe execution program and data generated by the execution program. Thecomputer may also include means such as a modem 34 and communicationssoftware for loading input data or the execution program from a remotelocation. As one skilled in the art will further appreciate, other typesof computers might be used such as a main frame, portable computer,note-book computer, or mini-computer.

C. In Operation

[0060] In operation, the user loads the execution program from theprogram memory storage location into the random access memory 30. Thoseskilled in the art will appreciate that the program might be stored onmagnetic media, (i.e., floppy disk drive, hard drive, or tape), readonly memory (i.e., optical disk), firm ware, or any other appropriatestorage medium 32. The program might also be transmitted from a remotelocation such as from a file server, a main frame, or other PC that hasa communication link with the user's terminal. Referring to FIG. 5, amenu is displayed on the computer screen after the program is loaded.The menu has the following options: Setup 36, Products 38, Time Value40, Management Spec's 42, Grow Out Spec's 44, Fixed/Variable Costs 46,Raw Materials 48, Choose Data Sets 50, Solve/Optimize 52, ManagementReport 54, Review/Predictions/Diets 56, Field Measurements 58, ModelCreation 60, Change Database 62, Use DOS Commands 64, and Exit to DOS(Quit) 66.

[0061] The first menu option is Setup 36. On invoking this option, auser with basic industry knowledge can define a new flock of birds oredit information concerning an existing flock. As shown in FIG. 6, theFlock Data computer screen 68 is displayed when the Setup menu item ischosen. From this screen, the user has four options. The user canhighlight an existing flock and press enter at which time the Flock DataMaintenance screen 70, FIG. 7, will appear on the display. At this timethe user can edit the displayed information, which includes the name ofthe farm 72 where the flock is kept; the name of the particular flock74; the entity from which the flock was purchased 76; a reference code78 that identifies the flock; the strain of bird that comprises theflock, model selector 80; and whether the user wishes to have automaticage calculation 82. Automatic age calculation calculates the age basedon the hatch date. The user can also choose to delete the listing of aparticular flock, or enter escape in order to return to the main menu.

[0062] The second item on the main menu is Products 38. Upon choosingthis menu item, the Electronic Data table (EDT) entitled “TABLE:PRODUCT.T” 84 is displayed. See FIG. 8. The information entered intothis EDT includes the price per pound for a whole bird, a guttedcarcass, and each of the individual body parts. The information enteredalso includes the amount of poultry product that the user wants to haveavailable for market. More specifically, the user enters the range ofacceptable product amount that he/she plans to market. If the user plansto market the poultry in parts, an acceptable range of product parts foreach type of part is entered. The price is entered into column 86, theminimum acceptable product amount is entered into column 88, and themaximum acceptable tonnage is entered into column 90.

[0063] The third item on the main menu is Time Value 40. Upon choosingthis menu item, a screen entitled “TABLE: TIME.T” 92 is displayed on thecomputer screen. See FIG. 9. The data that is entered into the EDTdisplayed in this screen includes, the age that the poultry will be sold94, the amount of time that a barn will be empty between flocks 96, thelength of the brooding period if the particular strain of birds has abrooding period 98, and the square foot the user wants to provide foreach bird within the barn 100. The unit of measurement for all timeperiods is days. The desired values are entered into the first column102 of the table if the user knows the precise time period or allowablesquare foot per bird. Otherwise the user can enter an acceptable rangeof time or square footage in the second and third columns 104 and 106.If the user enters a range, the program will calculate the optimum valuein order to maximize the user's return on investment.

[0064] The fourth item on the main menu is Management Spec's 42. Uponchoosing this menu item, the EDT entitled “INFORMTN.T” 108 is displayedon the screen. See FIG. 10. Information in this EDT is broken down intoa plurality of time intervals during the life of the poultry. Eachinterval is called a series 110 and corresponds to a production period.In the column entitled “Age, Days” 112 the user can enter the age of theflock at the end of each interval. In the column entitled “TEMP (F)” 114the user can enter the ambient temperature of the flocks environment. Inthe column entitled “HUMIDITY, %” 116 the user can enter the humidity ofthe flock's environment. One skilled in the art will realize that dataconcerning other environmental factors also may be included in theINFORMTN.T table 108.

[0065] The fifth item on the main menu is Grow Out Spec's 44. Uponchoosing this item, an EDT entitled “RECOMEND.T” 110 is displayed. SeeFIG. 11. Information in this table is broken down into a plurality oftime intervals 112 during the life of the poultry. Each interval iscalled a series and corresponds to a production period.

[0066] The sixth item on the main menu is Fixed/Variable Cost 46. Uponchoosing this item, the EDT entitled “COST.T” 126 is displayed. See FIG.12. Data listed in this table includes “FIX, $/YR” 128, which is fixedcosts per year; “PRCSS, $/YR” 130, which is the cost of processing peryear; “CHICK, $/BD” 132, which is the cost of purchasing each chick;“MARKT, $/YR” 134, which is the cost of marketing per year; “PRPNE,$/YR” 136, which is the cost of building heat per year; “BROOD, $/FL”138, which is the cost of brooding each flock of birds if the flock isof the type that requires brooding; and “GRWER, $/LB” 140, which is thecost of live weight per pound for contract grower.

[0067] The seventh item on the main menu is Raw Materials 48. Uponselection of this item, a sub-menu entitled “Raw Materials” 142 isdisplayed. See FIG. 13. The first item on the sub-menu is Select andPrice Ingredients 144. Upon selecting this first sub-menu item, the EDTentitled “INGREDIENT UPDATE” 146 is displayed. See FIG. 14.

[0068] The table includes columns entitled AVAIL. 147, GROUP 148, SHORTNAME 150, MIN 152, MAX 154, CTRL 156, COST 157/CWT, NO 158, and HA 160.The AVAIL. 140 column lists whether that particular ingredient isavailable to be included in the feed. As shown in FIG. 15, the possiblelistings in this column include Avail 162, which means that theingredient is available to the user; Maybe 164, which means that theingredient has a high price and the computer will try to use analternative ingredient; No 166, which means that the ingredient is notavailable to the user; and Cost 168, which means ingredient will not beused in formulation but the computer will give a price at which theingredient could be used. The GROUP column 148 lists the classificationof ingredients. The SHORT NAME 150 column lists the common name of theingredient. The MIN column 152 lists the minimum amount of thatingredient that the user wants to include in the feed. The units ofmeasurement for this data is percentage. The MAX column 154 lists themaximum amount of the ingredient that the user wants to include in thefeed. The CTRL column 156 marks those settings that cannot be changed byuser in this screen. The COST/CWT column 157 lists the cost of eachingredient per 100 pounds. The NU column 158 lists the choice ofpredicting nutrient level. The HA column 160 lists hand add value. Aswill be discussed in more detail below, an ingredients database liststhe types and amounts of the nutrients that are included in eachingredient. The amount of each ingredient listed in the databasecorresponds to the amount of ingredient that is found in a typical cropthat has a standard weight per bushel. One skilled in the art willfurther realize that the amount of each nutrient can vary with theweight of the crop per bushel. Thus, the program of the presentinvention has the capability of recalculating the amount of nutrients ineach ingredient if the weight per bushel is entered into the computer.

[0069] The eighth item on the main menu is Choose Data Sets 50. Whenthis item is chosen, the “TO BE FORMULATED” 170 screen is displayed. SeeFIG. 16. This menu option allows a user to select the particular flockthat is to be optimized.

[0070] The ninth item on the main menu is Solve/Optimize 52. When thisitem is chosen, the computer of the present invention will calculate theoptimum rate of growth. The computer will make these calculations foreach designated time interval during the life of the flock. The computerwill simultaneously calculate the optimal diet, living environment, andage at which the flock should be sold. The diet consists of the amountof ingredients that should be included in the feed. The livingenvironment includes the number of birds that are included in each flockand the density of the birds (e.g., the square feet per bird within thebarn). The age of the bird is the number of days between the birth ofthe birds and the date at which the bird should be sold to a processingplant. One skilled in the art will realize that the computer alsocalculates data concerning the volume of poultry that each flock willgenerate and financial data concerning the amount of revenue, costs, andreturn on investment. One skilled in the art will further realize thatother financial data may be calculated by the computer

[0071] The tenth item of the main menu is Management Report 54. Uponselection of this menu item, a list of the possible reports 172 isdisplayed on the screen. See FIG. 17. There are seven reports that theuser can choose. The first report is entitled OPTIMUM RESULTS 174 andlists the optimal performance and environmental constraint to which theuser must conform in order to realize the maximum possible Return OnInvestment. One skilled in the art will realize that such data includesthe optimal flock size, the optimal age at which the flock should besold, the optimal bird density in units of bird per square foot, theweight of the bird at sale, etc. The second report is entitled OPTIMUMPERFORMANCE 176 and includes data that relates to the length of eachfeeding period, the amount of feed given to the flock, the amount offeed that is consumed by the flock, etc. The third report is entitledOPTIMUM YIELD 178 and includes data that relates to the total weight ofthe flock that is available for sale, the costs of raising the flock,and the price received for the flock. The fourth report is entitledOPTIMUM FD/FACTORS 180 and includes information that relates to theamount and cost of the feed that a flock will consume. The fifth reportis entitled OPTIMUM NUT/ALLNCE 182 and includes information that relatesto the optimal nutrient amounts that need to be consumed and that can bemetered to a flock. The sixth report is entitle RESOURCES RAW/MATRLS 184and includes information related to the amount of ingredients that areconsumed and inventoried for use by a flock. The seventh report isentitled OPTIMUM INDIV-BIRD 186 and includes information related to thecharacteristics of the birds in each flock, its yield characteristics,the environmental conditions in which the flock will live, the averagesize of each bird within the flock, and the average amount of feedconsumed by each bird within the flock. Samples of the reports that aregenerated are shown in FIGS. 18a-18 g and labeled 174′, 176′, 178′,180′, 182′, 184′, and 186′, respectively.

[0072] The eleventh item on the main menu is Review/Predictions/Diets56. When this item is selected, the computer of the present inventionwill display the predicted value of data concerning the weight of theflock, the amount of feed consumed, the weight of the various part of abird, and other miscellaneous data concerning the environment of theflock. See FIG. 19. This information may also be updated to reflectactual data during the life of a flock. Upon entering the actual values,the SOLVE/OPTIMIZE 52 menu item may be re-selected in order to updatethe optimal diet, living environment, and age at which the flock shouldbe sold.

[0073] Preferably, the computer of the present invention is programmedusing the Clarion database software. Clarion is published by ClarionSoftware Corporation, which is located in Pompano Beach, Fla. Oneskilled in the art will realize that other database software packagessuch as Paradox, DB2, Access, etc., may be used. One skilled in the artwill further realize that the computer may also be programmed using theC, Fortran, Pascal or other programming languages. During execution ofthe program, the microprocessors sequentially executes each individualinstruction. However, as described herein, the operation of themicroprocessor implementing the program will be defined in terms ofmajor functional steps.

[0074] Referring to FIG. 20, the program that controls the computer ofthe present invention begins at block 200. The user may inputinformation into the databases at Block 202. The information inputtedmay enter either the Journal database 204, Ingredient database 206, orModel database 208. The Journal database, block 204, stores informationthat relates to the characteristics of the flock such as sex, weight,number, strain, etc. This database also stores the information that isgenerated by the model and the optimizer. Such information relates tothe optimal diet, environmental conditions, flock size, predictedmortality rate, predicted yield, financial figures, etc. The Ingredientdatabase, block 206, stores information that relates to the potentialingredients that may be included within the feed and the nutritionalvalues of the various ingredients. One skilled in the art will realizethat the Ingredient database also includes equations that the user canexecute to recalculate the value of the amino acid nutrients andmetabolizable energy. These equations are based on the weight per busheland the protein content of the ingredients. The model database, block208, includes information that relates to the actual code of theexecution files. The model database also includes information thatrelates to the variables that are used within the execution files.

[0075] One skilled in the art will realize that the blocks 210, 212,214, 216, 218, and 220 represent the various execution programs that arerequired to control the computer of the present invention. One skilledin the art will further realize that any one of these block may containa plurality of execution files in order to fulfill its function. Asdescribed above, the execution files and the databases are preferablywritten utilizing the Clarion database software.

[0076] At block 212, the user may execute the model that forms theequations that are described in the section above titled A. Theory. Thissection also forms equations that calculate the predicted mortality rateand other effects of living conditions, predicted yield for variouseconomic body parts, and nutrient calculations. More specifically, themodel will create a plurality of simultaneous equations that it willpass through the interface, block 222, to the Optimizer, block 224.

[0077] The interface, Block 222, reconfigures the information generatedby the Model, Block 212, into a form that is acceptable by theOptimizer. The interface is preferably written in C. The optimizershould be a non-linear optimizer, which are well known in the art.

[0078] The Optimizer, Block 224, will solve the simultaneous equationsin order to create the optimal values for each of the variables thatdescribe the predicted mortality rate and other effects of livingconditions, predicted yield for various economic body parts, andnutrient calculations. This information is then passed to the Journaldatabase, Block 204, where it is stored.

[0079] At block 210, the user may execute the files that generate andprint reports. These reports are described in detail above. At block214, the user may edit the tables that store information about thevarious ingredients that may be included in feed. More specifically, theuser may delete or add ingredients, and edit the nutritional valuesassociated with each ingredient. Additionally, the user may executeamino acid and energy equations that recalculates the values of theamino acid and metabolizable energy nutrients based on the weight perbushel and protein content of each ingredient. The informationmanipulated by block 214, is stored in the Ingredient database, block206.

[0080] At block 216, the user may create variables that are used in thevarious execution files. One skilled in the art will realize that atblock 218 the user may create and edit the various EDT tables that areused to organize and store information within the databases. Finally,the user may create and edit the execution files and databases at block220.

[0081]FIGS. 21a and 21 b describe the information flow of the programexecution. The information flow is shown generally at 300. Block 301illustrates the various inputs into the logical program flow in order tocalculate and solve the various equations. Block 302 includesinformation on nutrient composition and digestibility which may bestored in the form of a look-up table or some other known databasestructure. This data is provided to block 307 where data and/orequations on the nutrient efficiency is stored. Additional informationis provided to block 307 from the growth model block 303 and thenutrient to support growth block 306. Each of the various blocks 302,307, 306, 305, and 304 provide data and equations to optimizer block 308which solves the equations in an optimized manner. The outputs ofoptimizer block 308 are provided to output block 309 which provides theresults to the journal database 204 (best seen in FIG. 20). Thisinformation is illustrated as including: optimum marketing age, block310; optimum raw material tonnage and mixes, block 311; optimum growth &yield of animals, block 312; optimum nutrient level/period feeding,block 313; and optimum animal space density & number, block 314.

D. Operation of the Model

[0082] Referring now to FIGS. 22a-22 ai, the program begins at block300. The mathematical constant e (e=2.71828) and a space correctionfactor (SPACE_FACTOR=1000) are established at block 302. If this is thefirst time the model is executed, set the age, temperature, humidityvalues from a table for the current conditions, and set the mortalitycorrection to zero, block 304. The sequence value is then set to thecurrent period, block 306.

[0083] If the sum of the percentage of males and females does not total100% (plus or minus 1%) indicate a failure in the program at block 308.The next step is to give the optimizer an impossible condition at block310 and indicate that this is the last of the series of passes, thus theuser does not see the incorrect values.

[0084] If the starting feed period begins when the animal is born orhatched, (P_FEED_START=1), block 312, set feed cost correction by bodyweight to zero (FDBWT=0), block 314. Then skip to block 342. If thestarting feed period begins at some point other than the birth of theanimal (P_FEED_START>1), block 316, update the (model) sequence numberand feed cost correction by body weight, blocks 318 and 320,respectively. Current condition information such as age, temperature andhumidity is then entered, block 322.

[0085] If this is not the first pass of the program skip to block 340.Otherwise, compare optimized body weights to the field body weights atblocks 324-334. More specifically, find the current age of the animals,look up the values in the age database and compare it to the real bodyweights (P_AVE_BWT). Also compute the standard deviation (REUSE1) in theweighed animals and the real age (REUSE3), block 324. Check for errorsat block 326 in order to eliminate faulty values for body weights basedon variation, and the number of animals weighed. Upon finding an error,set the standard deviation to a very large number, block 328. If thestandard deviation is more than two or less than negative two, add theequation for weight at the beginning of the current period (WTB) withthe equations in block 332. Otherwise add the equation for weight at thebeginning of the current period (WTB) with the equations in block 334.

[0086] Compute the field mortality correction (MORT_FLD_CORRCT) at block336. If it is more than four or less than negative four, set it to zeroat block 338. Add equations to the model for the number of birds placed,block 340.

[0087] At block 342, set the beginning age (AGEB) to be the current age(AGE) and set the feeding period (FEEDING_PERIOD) to be 0. At block 344,set the ending age (AGEE) of the current sequence to be the beginningage of this sequence as found in the database provided and accumulateit. Do the same step for the feeding period. Retrieve the temperaturefor the sequence (TEMPFE) from the database, block 346.

[0088] Next, set the minimum and maximum market age. If the market lockage is zero, block 348, and the ending age of the sequence is greaterthan the minimum allowed market age, block 350, indicate that this willbe the end of the series of passes through the program (ESERIES=SERIES),block 352. Also at block 352, add equations that set the range for themarket age, setup values for the market range (MKTRGE) and the beginningmarket ages (MKTB, step 32). If the market lock age is not zero. block354, and the ending age of the sequence is greater than the maximumallowed market age, block 356, indicate that this will be the end of theseries of passes through the program (ESERIES=SERIES), block 358. Alsoat block 358, add equations that set the range for the market age, setthe market range to one day period and market beginning day equal to oneday less than locked market age.

[0089] If SERIES=ESERIES add an equation for the period as shown inblock 360. If SERIES does not equal ESERIES, add an equation for theperiod as shown in block 362.

[0090] At block 364, set the age for the diet formulation(FORMULATING_AGE) equal to the age at the middle of the current period.Then compute the beginning mortality (for current conditions) for themales and females depending on the respective percentages and add in thecorrection factor. At blocks 366-372, compute the mortality for each dayfrom the beginning of the period until the end of the period and add theresults to get the cumulative mortality. At block 374, divide thecumulative value by the number of days in order to obtain theincremental mortality (MORTINC).

[0091] Also compute the effective temperature at block 374. However, ifthe age of the current diet formulation is less than 21 days, block 376,retrieve the value of the effective temperature from the referencetemperature table for the current conditions, block 378. Next computethe adjustment period for temperature effects on body weight at block380-384. At block 386, add that correction factor to the totalcorrection factor for body weight affected by temperature(BW_TEMP_TOTAL), and setup the period over which the correction factoris applied (BW_TEMP_PERIOD).

[0092] If this is not the end of the series skip to block 400. If thefeed starting period is at the beginning, skip to block 398. Otherwise,summarize uptodate temperature effects on body weight (block 392) andthe number of days from a table (BW_TEMP_PERIOD) (block 394). At block398, add an equation to the model for the body weight temperaturecorrection (TEMPBW).

[0093] At block 400, compute the weight at maturity (MATUWT), place aconstraint for minimum age at maximum gain (AGEMG_LB), and maximum agesat maximum gain (AGEMG_UB). Additionally, add an equation to the modelfor the animal density (DNSITY). If the feed starting period is not thefirst, block 402, add an equation to the model that indicates massdensity (MDNSTY whose units are sq. meter/kg{circumflex over ( )}0.67)is greater than a very small number, block 404. Otherwise calculate thelower limit of the mass density at block 406. At block 408, set an upperlimit on the mass density and then add an equation to the model for thecorrection factor for body weight as a function of bird density (DNBW).If the ending age for the period is less than 35 days, block 410, setthe mortality as a function of body weight (BWMORT) and mortality due todensity (DNMORT) to zero, block 412. Otherwise they are calculated ineither block 414 or 416. More specifically, if this is the end of theseries use the equations for BWMORT and DNMORT in block 414, which arebased on the market age (MKTAGE). Otherwise the use the equations inblock 416, which are based on the ending age (AGEE) for the currentperiod.

[0094] At block 418, add an equation to the model to take into effectthe blistering on the breast of the bird.

[0095] If this is the end of the series, block 420, add equations to themodel for number of birds at processing time (FINUMB) and the averagenumber of birds in the period (DBIRD) based on the market age (MKTAGE),block 422. Otherwise, only add an equation for DBIRD based on the endingage of the current period, block 424.

[0096] If this is the last of the series, block 426, and the first timefor the feed formulation (P_FEED_START=1), block 428, then add equationsfor animal density as provided in tables, blocks 430 and 432. If theuser has supplied a fixed animal density, use it (block 430) otherwiseset the constraints in minimum and maximum as found in a table (block432).

[0097] At step 434, set constraints in the model for the maximum andminimum weight at market time from a table. If the objective is theweight of the carcass without giblets (W.O.G.), add equations foreviscerated carcass yield at block 436. If the objective is cut upparts, set constraints on breast yield at block 438.

[0098] If this is not the last of the series skip to block 448.Otherwise, add equations to the model that effect the body weight lossfrom fasting (FASTLS) during the time that it is being taken to market,block 440. Additionally, find the percentage of skin on breast (BRESKN)and neck (NECKSKIN) from tables for the current conditions. Use thesecorrections in equations that are added to the model for breast bone(BREBON), market weight (MKTWT), and yield (YIELD).

[0099] If the objective is cut up parts, add an equation for waste(WASTE), either block 442 or 444. Next, add the equations for breast,neck, drumsticks, thighs, wings, and back to the model, block 446. Thenadd the equations to the model for the Gompertz rate factor (RATEF) andthe rate factor for potential growth (PRATEF), block 448.

[0100] Depending on whether this is the first period in the sequence,add the equations from either block 450 or 452 to the model. Theseblocks included different variations for the equations for the weight atthe beginning (WTB) of the period, weight at beginning of the period(WTPB) for potential growth curve, and age at the beginning for maturity(AGEMTB). Similarly add an equation for the weight at the end (WTE),block 454 or 456. At block 458, add the equations to the model for theweight at ending period for potential growth(WTPE) and set the weight atthe beginning period of potential growth equal to the weight at thebeginning of optimized growth.

[0101] If the feed type is not zero, block 460, use 90% of amino acidavailability as a standard parameter, block 462. Otherwise the standardavailability of amino acids is 100%, block 458. At block 464, addequations for the standard deviation for body weight (STD), the numberof standard deviations for average gain in body weight (STDNO), fractionof normal curve (FRAC), and efficiency of non-linear gain (UTILG).

[0102] Depending on whether the animal's age is less than ten days, addequations for protein gain and feather gain set forth in block 468 or470.

[0103] At block 472, add the equations for the total gain (TOTALG),extra gain (EXTRAG) and the average metabolic weight (METAWT). Thenobtain the amino acid content for maintenance (AA_M), weight gain (AA_G)and feather gain (AA_F) from the database for Arginine, Lysine,Histidine, Isoleucine, Leucine, Methionine and Cystine combination,Methionine, Phenyalanine and Tyrosine combination, Phenyalanine.,Threonine, Tryptophan, and Valine. Add constraints for each of thesenutrients to the model at blocks 472-490, respectively.

[0104] The next step is to add equations for fat gain (FATG), feedintake (FI) and nutrient Metabolizable Energy (N002) to the model, block492. Then add constraints for period and accumulating effect ofmetabolizable energy on body weight taking into account nutritionaldensity and feed form at this point (MEBW and MEBWT), block 494.

[0105] If the user is reoptimizing, block 496, compute the feed cost tothe present (FD_COST_TO_NOW), block 498. For each sequence from thebeginning of the period, look up the effect of metabolizable energy ongains in the sequences, the feed costs in the database, and sum themtogether. The user is reoptimizing if the feed start period is not thefirst period.

[0106] Depending on the current pass in the series, compute the effectof metabolizable energy on weight gain (MEBWT) by adding up themetabolizable energy weights from the previous passes and one in thecurrent pass and dividing the sum by the lengths of the periods of theprevious passes, blocks 500-546.

[0107] At block 548, add the equations to the model for body weightcorrection that is dependent on metabolizable energy and the feed form(MEFFBW).

[0108] In the first pass in the series, set the values of the periodbody weight and the number of the period to zero, block 550. Then lookup the effect of period on body weight in the database at block 552. Ifthe feeding period is greater than 7 take into account the effect of thelength of the feeding period on growth, block 554. If this is the lastof the series of passes, compute the average effect of body weight forthe entire cycle (PRDBWT), block 556.

[0109] The next step is to obtain the standard metabolizable energyvalues (MESTD) and calculate the standard metabolizable energymaintenance coefficient for the current conditions (dependent on animalage). This task is accomplished by looking up the value for males andfemales in the database and multiplying by the respective percentages,blocks 558-568. Then add an equation to the model for the metabolizableenergy at 65 degrees Fahrenheit (ME65F), block 570.

[0110] Then change the standard intake of calcium, phosphorus, sodiumand chlorine by adjusting it to the 65 degree fahrenheit energy levels.Next add the constraints for each nutrient (N014 and N016) blocks 570and 572. An equation for the number of cycles per year (CYCLE) is thenadded to the model, block 572.

[0111] In order to speed up computations, some initial values areprovided at blocks 574 and 576 for AGEMG, RATEF, BWTB, BWTE, FAT, ME,which allow the system to make some initial guesses. If this is the endof the series, add different guesses for BWTE, ME, FINUMB, STNUMB,MKTWT, RATEF, YIELD, and BREAST at block 578. Then add guesses for N002,METAWT, FI, STDNO, WTB, WTE, WTPB, WTPE, AGEMTB, and METRUE at block580. If this is the last pass in the series add guesses for MEFFBW andMEBWT at block 582.

[0112] If market lock age was not set by the user, guess the market ageto be half way between the maximum and minimum market age, block 584.Otherwise set it be the lock age, block 586. At block 588, set guessvalues for DNSITY, MDNSTY and MKTAGE.

[0113] Finally, the system sets the parameters for the optimizer. Theoptimization package has tunable parameters that are set at block 590 toprovide better performance. Equations for flock parameter (FSIZE) arethen added to the model at block 592.

[0114] At block 592, price information is the retrieved from thedatabase market weight of animal, and prices for various parts are set.Also look up the fixed enterprise costs and the sub-objective to beoptimized. If the objective is cut up parts, look up the price of wastedproduct at block 594. If the objective selected by the user is tomaximize the live bird weight, add the equations of block 596 to themodel in order to constrain the sub-objectives and the maximum return oninvestment. If the objective selected by the user is to maximize theeviscerated carcass weight, add the equations of block 598 to the modelin order to constrain the sub-objectives and the maximum return oninvestment. If the objective selected by the user is to maximize theprice of the body parts, add the equations of block 600 to the model inorder to constrain the sub-objectives and the maximum return oninvestment.

[0115] Then obtain the minimum and maximum requirements from thedatabase for the available feed ingredients, blocks 602-608.

[0116] While the invention and method has been described in conjunctionwith a specific embodiment thereof, it is evident that differentalternatives, modifications, and variations will be apparent to thoseskilled in the art in view of the foregoing description. Accordingly,the invention is not limited to these embodiments or the use of elementshaving specific configurations as presented herein.

The claimed invention is:
 1. A method of determining the optimum growthof an animal, the method comprising the steps of: (a) determining aplurality of equations representing a growth rate and yield of edibletissue of the animal, wherein each of the equations identifies thegrowth rate and yield given genetic and non-genetic characteristics; (b)simultaneously solving the equations to optimize the growth rate andyield of the animal, thereby determining living factors of thenon-genetic characteristics and optimized values; and (c) controllingthe living factors of the non-genetic characteristics in accordance withthe optimized values thereby optimizing the age at which the animalachieves an optimum rate of growth.
 2. The method of claim 1 wherein thestep of determining the plurality of equations includes determining aplurality of equations having the form: W=Ae{circumflex over( )}(−e{circumflex over ( )}(−k(t−t*))) where W is the current bodyweight of the animal, A is the weight of the animal at physicalmaturity, t is the current age of the animal, and t* is the age at whichthe animal achieves its maximum rate of growth, and k is a growth ratefactor, t* and k being statistically related.
 3. The method of claim 1further comprising the step of optimizing the ratio between expendituresrequired to control the living factors of the non-geneticcharacteristics and the growth rate for the animal.
 4. The method ofclaim 3 wherein the life of the animal is divided into a plurality ofintervals, further wherein the step of optimizing the ratio betweenexpenditures required to control the living factors of the non-geneticcharacteristics and the growth rate for the animal is determinedaccording to the equations: W=Ae{circumflex over ( )}(−e{circumflex over( )}(−k(t 1−t*)))W=Ae{circumflex over ( )}(−e{circumflex over ( )}(−k(t2−t*))) where t1 is the age of the animal at the beginning of theinterval and t2 is the age of the animal at the end of the interval. 5.The method of claim 3 further comprising the steps of determining anoptimal diet based on the solution of the simultaneous equations andthen feeding the animals according to the optimal diet.
 6. The method ofclaim 5 wherein the step determining the optimal diet includes the stepof determining the optimal amount of nutrients to feed the animals. 7.The method of claim 6 wherein the step of determining the optimal dietincludes the step of determining the feed ingredients that contain thenutrients and the step of determining the amount of feed to provide theanimals.
 8. The method of claim 3 wherein the step of determining theoptimized values for the living factors of the non-geneticcharacteristics includes the step of determining an age at whichadditional growth of the animal has reached a point of diminishingreturn.
 9. The method of claim 8 comprising the additional step ofslaughtering the animal when it has substantially reached the age atwhich additional growth of the animal has reached a point of diminishingreturn.
 10. The method of claim 3 wherein the animals are raised in afacility having a predetermined amount of floor space, further whereinthe step of determining the optimized values for the living factors ofthe non-genetic characteristics includes the step of determining anoptimal density for a population of the animals.
 11. The method of claim3 wherein the step of determining the optimized values for the livingfactors of the non-genetic characteristics includes the steps ofdetermining the combined population weight of the animals anddetermining the individual weight at which additional growth of theanimals has reached a point of diminishing return.
 12. A method ofraising a population of animals for slaughter according to a pluralityof controllable factors, the method comprising the steps of: (a)inputting data corresponding to the controllable factors; (b) generatinga model that describes the growth rate of the population of animalsgiven variables that corresponds to the controllable factors; (c)establishing values for the variables thereby defining the controllablefactors; and (d) controlling the controllable factors as defined by thevalues for the variables so that the growth rate of the population ofanimals is optimized, wherein an aggregate mature weight of thepopulation and expenditures required to raise the populationsubstantially maximize the pre−tax net margin.
 13. The method of claim12 wherein the controllable characteristics include environmentalconditions and the step of controlling the controllable factors includesthe step of controlling the environmental conditions as established bythe values for of the variables.
 14. The method of claim 13 wherein theenvironmental conditions are in the group consisting of: temperature,humidity, population density, ventilation, disease conditions, and airquality.
 15. The method of claim 12 wherein the controllablecharacteristics include nutrition and the step of controlling thecontrollable factors includes the step of feeding the population ofanimals a type and quality of feed as established by the values for ofthe variables.
 16. The method of claim 12 wherein the step of generatingthe models includes the step of generating simultaneous equations havingthe form: W=Ae{circumflex over ( )}(−e{circumflex over ( )}(−k(t−t*)))where W is the current body weight of the animal, A is the weight of theanimal at physical maturity, t is the current age of the animal, and t*is the age at which the animal achieves its maximum rate of growth, andk is a growth rate factor, k and t* being statistically related.
 17. Themethod of claim 16 comprising the additional step of dividing the lifeof the animal into a plurality of intervals and the step of generatingmodels includes the step of generating a plurality of simultaneousequations having the form: W=Ae{circumflex over ( )}(−e{circumflex over( )}(−k(t 1−t*)))W=Ae{circumflex over ( )}(−e{circumflex over ( )}(−k(t2−t*))) where t1 is the age of the animal at the beginning of theinterval and t2 is the age of the animal at the end of the interval. 18.The method of claim 12 wherein the step of controlling the controllablecharacteristics includes maximizing the net margin of the population ofanimals.
 19. A computer apparatus for optimizing the rate of growth foran animal, the computer system comprising: (a) input means for inputtingdata; (b) a dataprocessor operatively connected to the input means, thedataprocessor including: i) generation means for generating a pluralityof simultaneous equations and for generating a variable for eachsimultaneous equation, wherein each simultaneous equation defines theage at which the animal can experience its optimal rate of growth givena predetermined characteristic, further wherein each variable is definedby the predetermined characteristic; ii) solution means for solving thesimultaneous equations; and iii) interface means for transferringgrowth-related information between the generation means and the solutionmeans; (c) a random access memory arranged and configured to store thesimultaneous equations and the variables for each characteristic; and(d) a storage medium arranged and configured to store the predeterminedcharacteristic that optimizes the age at which the animal reaches itsmaximum rate of growth, wherein the predetermined characteristicssubstantially maximize the net margin realized from the population ofanimals.
 20. The apparatus of claim 19 wherein the simultaneousequations have the form: W=Ae{circumflex over ( )}(−e{circumflex over( )}(−k(t−t*))) where W is the current body weight of the animal, A isthe weight of the animal at physical maturity, t is the current age ofthe animal, and t* is the age at which the animal achieves its maximumrate of growth, and k is a growth rate factor, k and t* beingstatistically related.
 21. The apparatus of claim 19 wherein the life ofthe animal is divided into a plurality of intervals, further wherein thedataprocessor generates equations having the form: W=Ae{circumflex over( )}(−e{circumflex over ( )}(−k(t 1−t*)))W=Ae{circumflex over( )}(−e{circumflex over ( )}(−k(t 2−t*))) where t1 is the age of theanimal at the beginning of the interval and t2 is the age of the animalat the end of the interval.
 22. The apparatus of claim 19 wherein eachsimultaneous equation defines the growth of one of the animals given apredetermined characteristic selected from the group consisting of:genetic characteristics, temperature, population density, diseaseconditions, type of feed, quantity of feed, humidity, ventilation, andair quality.
 23. The apparatus of claim 19 wherein the dataprocessor isfurther configured to optimize the ratio between expenditures requiredto control the predetermined characteristics and the rate of growth forthe animal.
 24. The apparatus of claim 23 wherein the dataprocessor isfurther configured to determine the optimal diet for the animal.
 25. Theapparatus of claim 24 wherein the storage medium stores nutritionalvalues for various types of feed ingredients, further wherein thedataprocessor is further configured to determine the optimal amount ofnutrients to feed the animals.
 26. The apparatus of claim 25 wherein thedataprocessor is further configured to determine the feed ingredientsthat contain the nutrients and determines the amount of feed to provedthe animal.
 27. The apparatus of claim 19 wherein the dataprocessor isfurther configured to determine the age at which additional growth ofthe animal has reached a point of diminishing return.
 28. The apparatusof claim 19 wherein the dataprocessor is further configured to determinea population density for a population of the animals.
 29. The apparatusof claim 19 wherein the dataprocessor is further configured to determinethe weight of the animals at which additional growth of the animal hasreached a point of diminishing return.
 30. An apparatus for optimizingthe rate of growth for an animal, the apparatus comprising: (a) firstprocessing means for generating a plurality of simultaneous equations,each equation defining the growth rate of the animal, the plurality ofsimultaneous equations for determining the optimal growth rate and yieldof the animals given predetermined characteristics; (b) secondprocessing means for generating a variable for each simultaneousequation, each variable defined by the predetermined characteristic; (c)third processing means for determining the predetermined characteristicsthat optimize the age at which the animal reaches its maximum rate ofgrowth; and (d) storage means for storing the predeterminedcharacteristics that optimizes the age at which the animal can reach itsmaximum rate of growth.
 31. The apparatus of claim 30 wherein the firstprocessing means generating equations having the form: W=Ae{circumflexover ( )}(−e{circumflex over ( )}(−k(t−t*))) where W is the current bodyweight of the animal, A is the weight of the animal at physicalmaturity, t is the current age of the animal, and t* is the age at whichthe animal achieves its maximum rate of growth, and k is a growth ratefactor, k and t* being statistically related.
 32. The apparatus of claim30 wherein the life of the animal is divided into a plurality ofintervals, further wherein the first processing means generatesequations having the form: W=Ae{circumflex over ( )}(−e{circumflex over( )}(−k(t 1−t*)))W=Ae{circumflex over ( )}(−e{circumflex over ( )}(−k(t2−t*))) where t1 is the age of the animal at the beginning of theinterval and t2 is the age of the animal at the end of the interval. 33.The apparatus of claim 30 further comprising fourth processing means foroptimizing the ratio between expenditures required to control thepredetermined characteristics and the rate of growth and yield for theanimal.
 34. The apparatus of claim 33 wherein the fourth processingmeans determines the optimal diet for the animal.
 35. The apparatus ofclaim 34 wherein the fourth processing means determines the optimalamount of nutrients to feed the animals.
 36. The apparatus of claim 35wherein the fourth processing means determines the feed ingredients thatcontain the nutrients and determines the amount of feed to provide theanimal.
 37. The apparatus of claim 30 wherein the fourth processingmeans determines the age at which additional growth of the animal hasreached a point of diminishing return.
 38. The apparatus of claim 30wherein the fourth processing means determines a population density fora population of the animals.
 39. The apparatus of claim 30 wherein thefourth processing means determines the weight of the animals at whichadditional growth of the animal has reached a point of diminishingreturn.
 40. A program storage device readable by a computer, tangiblyembodying a program of instructions executable by the computer toperform method steps for determining the optimum growth of an animal sothat the net margin of an enterprise that raises a population of theanimals can be substantially maximized, the method comprising the stepsof: (a) determining a plurality of equations representing a growth rateand yield of edible tissue of the animal, wherein each of the equationsidentifies the growth rate and yield given non-genetic characteristics,the plurality of equations being simultaneously solvable in order todetermine living factors of the non-genetic characteristics andoptimized values, wherein controlling the living factors in accordanceto the optimized values will optimize the age at which the animalachieves an optimum rate of growth; and (b) optimizing the ratio betweenexpenditures required to control the living factors and the growth ratefor the animal.
 41. The program storage device of claim 40, wherein thestep of determining the plurality of equations includes determining aplurality of equations having the form: W=Ae{circumflex over( )}(−e{circumflex over ( )}(−k(t−t*))) where W is the current bodyweight of the animal, A is the weight of the animal at physicalmaturity, t is the current age of the animal, and t* is the age at whichthe animal achieves its maximum rate of growth, and k is a growth ratefactor, t* and k being statistically related.
 42. The program storagedevice of claim 41, wherein the life of the animal is divided into aplurality of intervals, further wherein the step of optimizing the ratiobetween expenditures required to control the living factors of thenon-genetic characteristics and the growth rate for the animal isdetermined according to the equations: W=Ae{circumflex over( )}(−e{circumflex over ( )}(−k(t 1−t*)))W=Ae{circumflex over( )}(−e{circumflex over ( )}(−k(t 2−t*))) where t1 is the age of theanimal at the beginning of the interval and t2 is the age of the animalat the end of the interval.
 43. The program storage device of claim 42wherein the method comprises the additional step of determining anoptimal diet based on the solution of the simultaneous equations. 44.The program storage device of claim 43 wherein the step of determiningthe optimal diet includes the step of determining the optimal type andamount of nutrients to feed the animals and determining the feedingredients that contain the determined type and amount of nutrients.45. The method of claim 3 wherein the step of determining the optimizedvalues for the living factors of the non-genetic characteristicsincludes the step of determining an age at which additional growth ofthe animal has reached a point of diminishing return.
 46. A computerprogram product, comprising: a computer usable medium having computerreadable program code means embodied therein for determining the optimumgrowth of an animal so that the net margin of an enterprise that raisesa population of the animals can be substantially maximized, the computerreadable program code means comprising: computer readable program codefor causing a computer to generate a plurality of simultaneousequations, each equation defining the growth rate of the animal, theplurality of simultaneous equations for determining the optimal growthrate and yield of the animals given predetermined characteristics;computer readable program code for causing a computer to generate avariable for each simultaneous equation, each variable defined by thepredetermined characteristic; and computer readable program code forcausing a computer to determine the predetermined characteristics thatoptimize the age at which the animal reaches its maximum rate of growth,wherein raising the population of animals according to the predeterminedcharacteristics will substantially maximize the net margin of theenterprise.
 47. The computer program product of claim 46 wherein eachsimultaneous equation has the form: W=Ae{circumflex over( )}(−e{circumflex over ( )}(−k(t−t*))) where W is the current bodyweight of the animal, A is the weight of the animal at physicalmaturity, t is the current age of the animal, and t* is the age at whichthe animal achieves its maximum rate of growth, and k is a growth ratefactor, k and t* being statistically related.
 48. The computer programproduct of claim 47 wherein the life of the animal is divided into aplurality of intervals, further wherein the simultaneous equations havethe form: W=Ae{circumflex over ( )}(−e{circumflex over ( )}(−k(t1−t*)))W=Ae{circumflex over ( )}(−e{circumflex over ( )}(−k(t 2−t*)))where t1 is the age of the animal at the beginning of the interval andt2 is the age of the animal at the end of the interval.
 49. The computerprogram product of claim 46 wherein the computer readable program codemeans further comprises computer readable program code for optimizingthe ratio between expenditures required to control the predeterminedcharacteristics and the rate of growth and yield for the animal.
 50. Thecomputer program product of claim 49 wherein the computer readableprogram code means further comprises computer readable program code fordetermining the age at which additional growth of the animal has reacheda point of diminishing return.